// Copyright (C) 2018-2022 Intel Corporation
// SPDX-License-Identifier: Apache-2.0
//

///////////////////////////////////////////////////////////////////////////////////////////////////

#include "test_utils.h"

#include <intel_gpu/primitives/input_layout.hpp>
#include <intel_gpu/primitives/gemm.hpp>

#include <cstddef>

using namespace cldnn;
using namespace ::tests;

TEST(gemm_gpu, basic_bfyx_t1) {
    auto& engine = get_test_engine();
    auto input = engine.allocate_memory({ data_types::f32, format::bfyx,{ 1, 1, 3, 4 } });
    auto input2 = engine.allocate_memory({ data_types::f32, format::bfyx,{ 1, 1, 1, 4 } });

    std::vector<float> input_data = {
        1.f, -2.f,  3.f,
        -4.f, 5.f,  6.f,
        1.f, 2.f, 3.f,
        3.f, 2.f, -1.f,

    };

    std::vector<float> input_data2 = {
        2.f,
        5.f,
        -4.f,
        -7.f,
    };
    set_values(input, input_data);
    set_values(input2, input_data2);

    std::vector<float> out_data = {
        -43.f, -1.f, 31.f
    };

    topology topology;
    topology.add(
        input_layout("input", input->get_layout())
    );
    topology.add(
        input_layout("input2", input2->get_layout())
    );
    topology.add(
        gemm("output", { "input", "input2" }, data_types::f32, true, false)
    );

    network network(engine, topology);
    network.set_input_data("input", input);
    network.set_input_data("input2", input2);
    auto outputs = network.execute();

    auto output = outputs.at("output").get_memory();
    cldnn::mem_lock<float> output_ptr(output, get_test_stream());

    EXPECT_EQ(output_ptr.size(), (uint32_t)3);
    for (uint32_t i = 0; i < out_data.size(); ++i) {
        EXPECT_FLOAT_EQ(output_ptr[i], out_data[i]);
    }
}
TEST(gemm_gpu, basic_bfyx_t2) {
    auto& engine = get_test_engine();
    auto input = engine.allocate_memory({ data_types::f32, format::bfyx,{ 1, 1, 4, 3 } });
    auto input2 = engine.allocate_memory({ data_types::f32, format::bfyx,{ 1, 1, 4, 1 } });

    std::vector<float> input_data = {
        1.f, -2.f,  3.f, -4.f,
        5.f,  6.f, 1.f, 2.f,
        3.f, 3.f, 2.f, -1.f,

    };

    std::vector<float> input_data2 = {
        2.f, 5.f, -4.f, -7.f,
    };
    set_values(input, input_data);
    set_values(input2, input_data2);

    std::vector<float> out_data = {
        8.f, 22.f, 20.f
    };

    topology topology;
    topology.add(
        input_layout("input", input->get_layout())
    );
    topology.add(
        input_layout("input2", input2->get_layout())
    );
    topology.add(
        gemm("output", { "input", "input2" }, data_types::f32, false, true)
    );

    network network(engine, topology);
    network.set_input_data("input", input);
    network.set_input_data("input2", input2);
    auto outputs = network.execute();

    auto output = outputs.at("output").get_memory();
    cldnn::mem_lock<float> output_ptr(output, get_test_stream());

    EXPECT_EQ(output_ptr.size(), (uint32_t)3);
    for (uint32_t i = 0; i < out_data.size(); ++i) {
        EXPECT_FLOAT_EQ(output_ptr[i], out_data[i]);
    }
}

TEST(gemm_gpu, basic_bfyx_t1t2) {
    auto& engine = get_test_engine();
    auto input = engine.allocate_memory({ data_types::f32, format::bfyx,{ 2, 1, 3, 4 } });
    auto input2 = engine.allocate_memory({ data_types::f32, format::bfyx,{ 2, 1, 4, 1 } });

    std::vector<float> input_data = {
        1.f, -2.f,  3.f,
        -4.f, 5.f,  6.f,
        1.f, 2.f, 3.f,
        3.f, 2.f, -1.f,

        1.f, -2.f,  3.f,
        -4.f, 5.f,  6.f,
        1.f, 2.f, 3.f,
        3.f, 2.f, -1.f,

    };

    std::vector<float> input_data2 = {
        2.f, 5.f, -4.f, -7.f,

        2.f, 5.f, -4.f, -7.f,
    };
    set_values(input, input_data);
    set_values(input2, input_data2);

    std::vector<float> out_data = {
        -43.f, -1.f, 31.f,
        -43.f, -1.f, 31.f
    };

    topology topology;
    topology.add(
        input_layout("input", input->get_layout())
    );
    topology.add(
        input_layout("input2", input2->get_layout())
    );
    topology.add(
        gemm("output", { "input", "input2" }, data_types::f32, true, true)
    );

    network network(engine, topology);
    network.set_input_data("input", input);
    network.set_input_data("input2", input2);
    auto outputs = network.execute();

    auto output = outputs.at("output").get_memory();
    cldnn::mem_lock<float> output_ptr(output, get_test_stream());

    EXPECT_EQ(output_ptr.size(), (uint32_t)6);
    for (uint32_t i = 0; i < out_data.size(); ++i) {
        EXPECT_FLOAT_EQ(output_ptr[i], out_data[i]);
    }
}

TEST(gemm_gpu, basic_input3) {
    auto& engine = get_test_engine();
    auto input = engine.allocate_memory({ data_types::f32, format::bfyx,{ 1, 1, 3, 2 } });
    auto input2 = engine.allocate_memory({ data_types::f32, format::bfyx,{ 1, 1, 2, 3 } });
    auto input3 = engine.allocate_memory({ data_types::f32, format::bfyx,{ 1, 1, 2, 2 } });
    float alpha = 2.f;
    float beta = 10.f;

    std::vector<float> input_data = {
        1.0f, 2.0f, 3.0f,
        1.0f, 0.0f, 1.0f
    };

    std::vector<float> input_data2 = {
        3.0f, 3.0f,
        1.0f, 2.0f,
        1.0f, 2.0f,
    };

    std::vector<float> input3_data = {
        1.0f, 0.0f,
        2.0f, 0.0f,
    };

    set_values(input, input_data);
    set_values(input2, input_data2);
    set_values(input3, input3_data);

    std::vector<float> out_data = {
        26.0f, 26.0f,
        28.0f, 10.0f
    };

    topology topology;
    topology.add(
        input_layout("input", input->get_layout())
    );
    topology.add(
        input_layout("input2", input2->get_layout())
    );
    topology.add(
        input_layout("input3", input3->get_layout())
    );
    topology.add(
        gemm("output", { "input", "input2", "input3" }, data_types::f32,  false, false, alpha, beta)
    );

    network network(engine, topology);
    network.set_input_data("input", input);
    network.set_input_data("input2", input2);
    network.set_input_data("input3", input3);
    auto outputs = network.execute();

    auto output = outputs.at("output").get_memory();
    cldnn::mem_lock<float> output_ptr(output, get_test_stream());

    EXPECT_EQ(output_ptr.size(), (uint32_t)4);

    for (uint32_t i = 0; i < out_data.size(); ++i) {
        EXPECT_FLOAT_EQ(output_ptr[i], out_data[i]);
    }
}

TEST(gemm_gpu, basic_input3_t1t2) {
    auto& engine = get_test_engine();
    auto input = engine.allocate_memory({ data_types::f32, format::bfyx,{ 1, 1, 4, 3 } });
    auto input2 = engine.allocate_memory({ data_types::f32, format::bfyx,{ 1, 1, 3, 2 } });
    auto input3 = engine.allocate_memory({ data_types::f32, format::bfyx,{ 1, 1, 2, 4 } });
    float alpha = 2.f;
    float beta = 3.f;

    std::vector<float> input_data = {
        1.0f, 2.0f, 3.0f, 4.0f,
        1.0f, 0.0f, 1.0f, 0.0f,
        0.0f, 0.0f, 0.0f, 0.0f
    };

    std::vector<float> input_data2 = {
        3.0f, 3.0f, 1.0f,
        2.0f, 1.0f, 2.0f,
    };

    std::vector<float> input3_data = {
        1.0f, 0.0f,
        1.0f, 0.0f,
        2.0f, 2.0f,
        1.0f, 1.0f,
    };

    set_values(input, input_data);
    set_values(input2, input_data2);
    set_values(input3, input3_data);

    std::vector<float> out_data = {
        15.0f, 6.0f,
        15.0f, 8.0f,
        30.0f, 20.0f,
        27.0f, 19.0f
    };

    topology topology;
    topology.add(
        input_layout("input", input->get_layout())
    );
    topology.add(
        input_layout("input2", input2->get_layout())
    );
    topology.add(
        input_layout("input3", input3->get_layout())
    );
    topology.add(
        gemm("output", { "input", "input2", "input3" }, data_types::f32, true, true, alpha, beta)
    );

    network network(engine, topology);
    network.set_input_data("input", input);
    network.set_input_data("input2", input2);
    network.set_input_data("input3", input3);
    auto outputs = network.execute();

    auto output = outputs.at("output").get_memory();
    cldnn::mem_lock<float> output_ptr(output, get_test_stream());

    EXPECT_EQ(output_ptr.size(), (uint32_t)8);

    for (uint32_t i = 0; i < out_data.size(); ++i) {
        EXPECT_FLOAT_EQ(output_ptr[i], out_data[i]);
    }
}
TEST(gemm_gpu, basic_input3_1) {
    auto& engine = get_test_engine();
    auto input = engine.allocate_memory({ data_types::f32, format::bfyx,{ 1, 1, 3, 4 } });
    auto input2 = engine.allocate_memory({ data_types::f32, format::bfyx,{ 1, 1, 2, 3 } });
    auto input3 = engine.allocate_memory({ data_types::f32, format::bfyx,{ 1, 1, 2, 4 } });
    float alpha = 2.f;
    float beta = 3.f;

    std::vector<float> input_data = {
        1.0f, 1.0f, 0.0f,
        2.0f, 0.0f, 0.0f,
        3.0f, 1.0f, 0.0f,
        4.0f, 0.0f, 0.0f
    };

    std::vector<float> input_data2 = {
        3.0f, 2.0f,
        3.0f, 1.0f,
        1.0f, 2.0f,
    };

    std::vector<float> input3_data = {
        1.0f, 0.0f,
        1.0f, 0.0f,
        2.0f, 2.0f,
        1.0f, 1.0f,
    };

    set_values(input, input_data);
    set_values(input2, input_data2);
    set_values(input3, input3_data);

    std::vector<float> out_data = {
        15.0f, 6.0f,
        15.0f, 8.0f,
        30.0f, 20.0f,
        27.0f, 19.0f
    };

    topology topology;
    topology.add(
        input_layout("input", input->get_layout())
    );
    topology.add(
        input_layout("input2", input2->get_layout())
    );
    topology.add(
        input_layout("input3", input3->get_layout())
    );
    topology.add(
        gemm("output", { "input", "input2", "input3" }, data_types::f32, false, false, alpha, beta)

    );

    network network(engine, topology);
    network.set_input_data("input", input);
    network.set_input_data("input2", input2);
    network.set_input_data("input3", input3);
    auto outputs = network.execute();

    auto output = outputs.at("output").get_memory();
    cldnn::mem_lock<float> output_ptr(output, get_test_stream());

    EXPECT_EQ(output_ptr.size(), (uint32_t)8);

    for (uint32_t i = 0; i < out_data.size(); ++i) {
        EXPECT_FLOAT_EQ(output_ptr[i], out_data[i]);
    }
}

TEST(gemm_gpu, basic_input3_t2) {
    auto& engine = get_test_engine();
    auto input = engine.allocate_memory({ data_types::f32, format::bfyx,{ 1, 1, 3, 4 } });
    auto input2 = engine.allocate_memory({ data_types::f32, format::bfyx,{ 1, 1, 3, 2 } });
    auto input3 = engine.allocate_memory({ data_types::f32, format::bfyx,{ 1, 1, 2, 4 } });
    float alpha = 2.f;
    float beta = 3.f;

    std::vector<float> input_data = {
        1.0f, 1.0f, 0.0f,
        2.0f, 0.0f, 0.0f,
        3.0f, 1.0f, 0.0f,
        4.0f, 0.0f, 0.0f
    };

    std::vector<float> input_data2 = {
        3.0f, 3.0f, 1.0f,
        2.0f, 1.0f, 2.0f,
    };

    std::vector<float> input3_data = {
        1.0f, 0.0f,
        1.0f, 0.0f,
        2.0f, 2.0f,
        1.0f, 1.0f,
    };

    set_values(input, input_data);
    set_values(input2, input_data2);
    set_values(input3, input3_data);

    std::vector<float> out_data = {
        15.0f, 6.0f,
        15.0f, 8.0f,
        30.0f, 20.0f,
        27.0f, 19.0f,
    };

    topology topology;
    topology.add(
        input_layout("input", input->get_layout())
    );
    topology.add(
        input_layout("input2", input2->get_layout())
    );
    topology.add(
        input_layout("input3", input3->get_layout())
    );
    topology.add(
        gemm("output", { "input", "input2", "input3" }, data_types::f32, false, true, alpha, beta)
    );

    network network(engine, topology);
    network.set_input_data("input", input);
    network.set_input_data("input2", input2);
    network.set_input_data("input3", input3);
    auto outputs = network.execute();

    auto output = outputs.at("output").get_memory();
    cldnn::mem_lock<float> output_ptr(output, get_test_stream());

    EXPECT_EQ(output_ptr.size(), (uint32_t)8);

    for (uint32_t i = 0; i < out_data.size(); ++i) {
        EXPECT_FLOAT_EQ(output_ptr[i], out_data[i]);
    }
}

TEST(gemm_gpu, basic_input3_t1) {
    auto& engine = get_test_engine();
    auto input = engine.allocate_memory({ data_types::f32, format::bfyx,{ 1, 1, 4, 3 } });
    auto input2 = engine.allocate_memory({ data_types::f32, format::bfyx,{ 1, 1, 2, 3 } });
    auto input3 = engine.allocate_memory({ data_types::f32, format::bfyx,{ 1, 1, 2, 4 } });
    float alpha = 2.f;
    float beta = 3.f;

    std::vector<float> input_data = {
        1.0f, 2.0f, 3.0f, 4.0f,
        1.0f, 0.0f, 1.0f, 0.0f,
        0.0f, 0.0f, 0.0f, 0.0f
    };

    std::vector<float> input_data2 = {
        3.0f, 2.0f,
        3.0f, 1.0f,
        1.0f, 2.0f
    };

    std::vector<float> input3_data = {
        1.0f, 0.0f,
        1.0f, 0.0f,
        2.0f, 2.0f,
        1.0f, 1.0f,
    };

    set_values(input, input_data);
    set_values(input2, input_data2);
    set_values(input3, input3_data);

    std::vector<float> out_data = {
        15.0f, 6.0f,
        15.0f, 8.0f,
        30.0f, 20.0f,
        27.0f, 19.0f,
    };

    topology topology;
    topology.add(
        input_layout("input", input->get_layout())
    );
    topology.add(
        input_layout("input2", input2->get_layout())
    );
    topology.add(
        input_layout("input3", input3->get_layout())
    );
    topology.add(
        gemm("output", { "input", "input2", "input3" }, data_types::f32, true, false, alpha, beta)
    );

    network network(engine, topology);
    network.set_input_data("input", input);
    network.set_input_data("input2", input2);
    network.set_input_data("input3", input3);
    auto outputs = network.execute();

    auto output = outputs.at("output").get_memory();
    cldnn::mem_lock<float> output_ptr(output, get_test_stream());

    EXPECT_EQ(output_ptr.size(), (uint32_t)8);

    for (uint32_t i = 0; i < out_data.size(); ++i) {
        EXPECT_FLOAT_EQ(output_ptr[i], out_data[i]);
    }
}

TEST(gemm_gpu, basic_bfyx) {
    auto& engine = get_test_engine();
    auto input = engine.allocate_memory({ data_types::f32, format::bfyx,{ 2, 1, 4, 3 } });
    auto input2 = engine.allocate_memory({ data_types::f32, format::bfyx,{ 2, 1, 1, 4 } });

    std::vector<float> input_data = {
        1.f, -2.f,  3.f,  -4.f,
        5.f,  6.f,  7.f,   8.f,
        -10.f, 12.f, 13.f, -13.f,

        1.f, -2.f,  3.f,  -4.f,
        5.f,  6.f,  7.f,   8.f,
        -10.f, 12.f, 13.f, -13.f,
    };

    std::vector<float> input_data2 = {
        2.f,
        5.f,
        -4.f,
        -7.f,
        2.f,
        5.f,
        -4.f,
        -7.f,
    };
    set_values(input, input_data);
    set_values(input2, input_data2);

    std::vector<float> out_data = {
        8.f, -44.f, 79.f, 8.f, -44.f, 79.f,
    };

    topology topology;
    topology.add(
        input_layout("input", input->get_layout())
    );
    topology.add(
        input_layout("input2", input2->get_layout())
    );
    topology.add(
        gemm("output", { "input", "input2" }, data_types::f32)
    );

    network network(engine, topology);
    network.set_input_data("input", input);
    network.set_input_data("input2", input2);
    auto outputs = network.execute();

    auto output = outputs.at("output").get_memory();
    cldnn::mem_lock<float> output_ptr(output, get_test_stream());


    EXPECT_EQ(output_ptr.size(), (uint32_t)6);
    for (uint32_t i = 0; i < out_data.size(); ++i) {
            EXPECT_FLOAT_EQ(output_ptr[i], out_data[i]);
    }
}

TEST(gemm_gpu, basic3_bfyx) {
    auto& engine = get_test_engine();
    auto input = engine.allocate_memory({ data_types::f32, format::bfyx,{ 5, 1, 500, 9 } });
    auto input2 = engine.allocate_memory({ data_types::f32, format::bfyx,{ 5, 1, 1, 500 } });

    std::vector<float> input_data = {
        -0.000449777f, -0.000137405f, -0.0762075f, 0.000949166f, 0.0346124f, -0.0111424f, 0.0108357f, 0.0121679f, 0.0242749f, 0.052692f, -0.0017713f, 0.0053728f, 0.0128862f, -0.0162366f, 0.0125041f, -0.00602398f, 0.0107778f, -0.00323086f, -0.00914208f, -0.013884f, 0.00755173f, -0.0175622f, 0.00473339f, -0.015003f, -0.0238219f, 0.004502f, 0.00187154f, 0.0041163f, -9.36184e-05f, 0.00873372f, 0.0121869f, -0.020973f, -0.006006f, -0.0038208f, 0.00210471f, 0.00255549f, -0.0251856f, -0.0626372f, -0.0059258f, -0.0058662f, -0.0946306f, 0.00197436f, 0.00105865f, -0.0033595f, 0.0158977f, -0.0036025f, -0.00568902f, -0.0202577f, -0.000251319f, -0.0117895f, -0.0144239f, -0.0144024f, -0.0150431f, -0.0354826f, -0.0135123f, -0.000422157f, 0.0286438f, -0.000884989f, -0.00675718f, 0.013241f, -0.0118388f, 0.0321394f, -0.000803071f, 0.11408f, -0.00806301f, -0.00831608f, 0.0165189f, 0.016094f, -0.000449332f, -0.00695901f, 0.0437514f, -0.00172117f, 0.00180391f, -0.000859933f, -0.0144826f, 0.0262613f, -0.00194352f, -1.98829e-05f, -0.00902827f, -0.00400867f, -0.00600827f, 0.0120846f, -0.0162493f, 0.0418596f, 0.00131911f, -0.00631566f, 0.00270484f, -0.0950513f, 0.00726431f, -0.0169798f, -0.000554365f, -0.00256903f, -0.00885843f, 0.0104025f, 0.00590779f, -0.00175832f, 0.0168603f, 0.00964353f, -0.0180614f, 0.0213157f, 0.0209548f, -0.0231143f, -0.00121617f, -0.0129815f, -0.0199287f, 0.00863336f, -0.00464991f, 0.0162288f, -0.340115f, -0.011018f, -0.0593997f, 0.00644821f, 0.0416332f, 0.0394596f, 0.0172296f, 0.00494231f, 0.0143805f, -0.00819845f, 0.00196982f, 0.00393258f, 0.0246168f, -0.0235927f, 0.0131416f, -0.0190432f, -0.0237865f, -0.0155627f, 0.0265165f, 0.0162884f, 0.00321098f, 0.0136674f, -0.000966112f, -0.0100813f, -0.00604589f, 0.00889466f, 0.0113945f, 0.0264707f, 0.00371883f, -0.00843358f, 0.0145675f, 0.0048638f, 0.00110399f, -0.00130233f, 0.00740726f, -0.00393368f, -0.0242178f, 0.00341681f, 0.00115369f, -0.00297881f, -0.0844071f, 0.0537151f, -0.00209399f, 0.0310295f, 0.0383914f, 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        -0.0730483f,
        0.60233f,
        -0.0485716f,
        0.445732f,
        -0.652175f,
        0.176092f,
        0.0424668f,
        -0.464009f,
        0.0419261f,
        0.437008f,
        -0.0949722f,
        0.322407f,
        0.00229612f,
        -0.0698273f,
        0.279531f,
        0.0615138f,
        0.029985f,
        0.0397836f,
        -0.0450066f,
        -0.153192f,
        -0.00434645f,
        0.235137f,
        -0.430068f,
        0.0479958f,
        0.0538638f,
        0.0335953f,
        0.059768f,
        -0.00594587f,
        0.313076f,
        0.173102f,
        -0.285881f,
        0.0860142f,
        -0.0656319f,
        0.0903421f,
        0.285596f,
        -0.00867567f,
        0.140828f,
        0.0679629f,
        -0.0386886f,
        -0.0432885f,
        -0.0523634f,
        -0.202516f,
        -0.393785f,
        0.0862689f,
        0.196867f,
        -1.25594f,
        0.407078f,
        0.0883489f,
        -0.145128f,
        -0.0270446f,
        -0.436027f,
        0.124345f,
        0.0216037f,
        -0.0341296f,
        -0.0550939f,
        -0.0143608f,
        0.269727f,
        -0.316092f,
        0.24142f,
        -0.0602843f,
        0.677077f,
        0.015578f,
        -0.0866818f,
        -0.0114968f,
        0.233375f,
        0.0768293f,
        -0.305731f,
        -0.101196f,
        0.116959f,
        -0.705778f,
        -0.274866f,
        0.0159985f,
        -0.0331097f,
        -0.165272f,
        0.00676643f,
        0.194435f,
        -0.644084f,
        -0.0719713f,
        -0.38506f,
        -0.0766179f,
        -0.232665f,
        -0.184962f,
        -0.0873918f,
        0.123643f,
        -0.10653f,
        -0.0842152f,
        0.173415f,
        0.0549799f,
        -0.246653f,
        -0.753266f,
        -0.17178f,
        -0.315154f,
        -0.284002f,
        -0.0944792f,
        0.513692f,
        -0.555574f,
        0.207956f,
        0.108376f,
        -0.322661f,
        -0.181751f,
        0.0175992f,
        -0.067274f,
        -0.0244339f,
        0.264443f,
        -0.307399f,
        0.435229f,
        -0.0912658f,
        0.41608f,
        0.203329f,
        0.0611729f,
        -0.11855f,
        -0.0901752f,
        0.219847f,
        -0.00417572f,
        2.35094f,
        0.0649107f,
        -0.0693629f,
        0.118256f,
        0.0929001f,
        -0.295607f,
        0.102728f,
        0.0786511f,
        -0.164747f,
        0.0778936f,
        0.269988f,
        -0.0515926f,
        0.147636f,
        -0.121939f,
        -0.0303203f,
        -0.702988f,
        -0.220738f,
        -0.104178f,
        0.102754f,
        -0.138891f,
        -0.202057f,
        -0.130212f,
        -0.0471592f,
        0.0441513f,
        -0.0329241f,
        0.124936f,
        0.0593826f,
        0.209008f,
        0.336101f,
        0.360896f,
        0.118351f,
        -0.169321f,
        -0.00791483f,
        -0.584241f,
        -0.507303f,
        -0.103466f,
        0.031976f,
        0.17687f,
        -0.0595649f,
        0.126475f,
        -0.046226f,
        0.143653f,
        -0.0457821f,
        0.0206962f,
        -0.0371797f,
        0.179695f,
        0.1175f,
        -0.551365f,
        0.187117f,
        -0.385674f,
        -0.983871f,
        -0.42516f,
        0.0679211f,
        -0.199898f,
        0.192904f,
        -0.0518964f,
        0.188334f,
        0.202665f,
        0.198246f,
        0.279775f,
        0.100275f,
        -0.13811f,
        0.161858f,
        -0.243149f,
        -0.0127482f,
        0.0757492f,
        -0.441334f,
        -0.0268542f,
        -0.114279f,
        -0.177216f,
        -0.0719604f,
        -0.127649f,
        -0.125531f,
        0.520186f,
        -0.0842066f,
        0.236264f,
        0.22663f,
        0.313905f,
        -0.26988f,
        0.188891f,
        -0.273121f,
        -0.339143f,
        0.251947f,
        -0.800452f,
        0.0130017f,
        0.0306637f,
        -0.488503f,
        0.368267f,
        -0.0427116f,
        0.0153203f,
        -0.16417f,
        -0.0864108f,
        0.153452f,
        0.37565f,
        0.431599f,
        0.145022f,
        0.0238288f,
        -0.344559f,
        0.170844f,
        0.220166f,
        0.0584108f,
        -0.0242578f,
        0.459242f,
        -0.309433f,
        -0.183178f,
        0.108402f,
        -0.558459f,
        -0.116711f,
        0.131252f,
        0.0709812f,
        0.158865f,
        -0.222513f,
        -0.0143199f,
        0.179904f,
        -0.325517f,
        0.0144405f,
        -0.248297f,
        0.0659974f,
        0.384588f,
        -0.12348f,
        0.0427167f,
        0.0150143f,
        -0.354596f,
        -0.276234f,
        0.0335361f,
        0.207341f,
        -0.456912f,
        -0.439884f,
        0.0628522f,
        -0.13091f,
        0.199357f,
        -0.218441f,
        -0.367666f,
        -0.0216214f,
        -0.069383f,
        -0.0200709f,
        -0.235768f,
        0.15368f,
        -0.177165f,
        -0.0735893f,
        0.0660757f,
        0.395157f,
        0.0614654f,
        -0.159744f,
        -0.245473f,
        -0.207488f,
        0.253759f,
        -0.0102803f,
        0.116993f,
        -0.0493576f,
        0.0167945f,
        0.138382f,
        -0.00102203f,
        -0.144797f,
        -0.222619f,
        0.320866f,
        0.0507977f,
        -0.0458033f,
        1.10501f,
        -0.116079f,
        -0.393548f,
        -0.320955f,
        -0.386687f,
        0.277903f,
        0.0759589f,
        -0.278561f,
        -0.162686f,
        -0.022386f,
        -0.244537f,
        0.0274179f,
        -0.080937f,
        -0.222133f,
        0.0633341f,
        0.155947f,
        -0.0298876f,
        -0.18921f,
        0.190984f,
        -0.35663f,
        -0.137884f,
        0.550159f,
        0.096353f,
        0.273687f,
        0.288882f,
        0.0811719f,
        0.279464f,
        0.168219f,
        -0.231556f,
        0.338719f,
        0.170307f,
        -0.04944f,
        1.94646f,
        -0.151242f,
        0.192923f,
        0.197884f,
        -0.193047f,
        -0.148041f,
        -0.0801752f,
        0.00753225f,
        -0.0705527f,
        0.10537f,
        -0.212792f,
        0.0661733f,
        0.00248664f,
        0.12624f,
        -0.622626f,
        0.106069f,
        0.0252939f,
        -0.0474646f,
        -0.0415958f,
        -0.207594f,
        -0.0870699f,
        0.0662641f,
        -0.172468f,
        0.152725f,
        0.118974f,
        0.471971f,
        -0.187808f,
        0.0202502f,
        -0.271737f,
        0.395173f,
        0.172049f,
        -0.115912f,
        0.293842f,
        -0.0161143f,
        0.268388f,
        -0.488364f,
        0.405653f,
        -0.318354f,
        0.226183f,
        -0.371718f,
        -0.124455f,
        0.114567f,
        -0.0197764f,
        -0.255166f,
        -0.151114f,
        -0.189752f,
        -0.674399f,
        -0.532053f,

    };
    set_values(input, input_data);
    set_values(input2, input_data2);

    std::vector<float> out_data = {
        1.4538f,  0.1023f,  0.9402f,  0.1373f, -0.5619f, -0.6068f, -1.4220f,
        -0.8573f,  0.9406f,

        1.3968f, -0.0450f,  0.7518f,  0.4434f, -0.2937f, -0.4165f, -0.8629f,
        -0.5942f,  0.4324f,

        1.3968f, -0.0450f,  0.7518f,  0.4434f, -0.2937f, -0.4165f, -0.8629f,
        -0.5942f,  0.4324f,

        1.3968f, -0.0450f,  0.7518f,  0.4434f, -0.2937f, -0.4165f, -0.8629f,
        -0.5942f,  0.4324f,

        1.3968f, -0.0450f,  0.7518f,  0.4434f, -0.2937f, -0.4165f, -0.8629f,
        -0.5942f,  0.4324f

    };

    topology topology;
    topology.add(
        input_layout("input", input->get_layout())
    );
    topology.add(
        input_layout("input2", input2->get_layout())
    );
    topology.add(
        gemm("output", { "input", "input2" }, data_types::f32)
    );

    network network(engine, topology);
    network.set_input_data("input", input);
    network.set_input_data("input2", input2);
    auto outputs = network.execute();

    auto output = outputs.at("output").get_memory();
    cldnn::mem_lock<float> output_ptr(output, get_test_stream());

    EXPECT_EQ(output_ptr.size(), (uint32_t)45);
    for (uint32_t  i = 0; i < out_data.size(); ++i) {
        EXPECT_NEAR(output_ptr[i], out_data[i], 0.0001);
    }

}

TEST(gemm_gpu, basic_smarcink2) {
    auto& engine = get_test_engine();
    auto input = engine.allocate_memory({ data_types::f32, format::bfyx,{ 2, 1, 3, 2 } });
    auto input2 = engine.allocate_memory({ data_types::f32, format::bfyx,{ 2, 1, 2, 3 } });

    std::vector<float> input_data = {
        1.0f, 2.0f, 3.0f,
        4.0f, 5.0f, 6.0f,

        1.0f, 1.0f, 1.0f,
        2.0f, 3.0f, 4.0f
    };

    std::vector<float> input_data2 = {
        7.0f, 8.0f,
        9.0f, 10.0f,
        11.0f, 12.0f,

        1.0f, 1.0f,
        1.0f, 1.0f,
        3.0f, 2.0f
    };
    set_values(input, input_data);
    set_values(input2, input_data2);

    std::vector<float> out_data = {
        58.0f, 64.0f,
        139.0f, 154.0f,

        5.0f, 4.0f,
        17.0f, 13.0f
    };

    topology topology;
    topology.add(
        input_layout("input", input->get_layout())
    );
    topology.add(
        input_layout("input2", input2->get_layout())
    );
    topology.add(
        gemm("output", { "input", "input2" }, data_types::f32)
    );

    network network(engine, topology);
    network.set_input_data("input", input);
    network.set_input_data("input2", input2);
    auto outputs = network.execute();

    auto output = outputs.at("output").get_memory();
    cldnn::mem_lock<float> output_ptr(output, get_test_stream());

    EXPECT_EQ(output_ptr.size(), (uint32_t)8);
    for (uint32_t i = 0; i < out_data.size(); ++i) {
        EXPECT_FLOAT_EQ(output_ptr[i], out_data[i]);
    }
}

struct gemm_base_test_params {
    size_t m_size;
    size_t n_size;
    size_t k_size;
    size_t b0_num;
    size_t f0_num;
    size_t b1_num;
    size_t f1_num;
    size_t b2_num;
    size_t f2_num;
    size_t b_out_num;
    size_t f_out_num;
    bool transpose_input0;
    bool transpose_input1;
    float alpha;
    float beta;
    cldnn::data_types allocate0_type;
    cldnn::data_types allocate1_type;
    cldnn::data_types allocate2_type;
    cldnn::data_types output_type;
    std::vector <int> range0;
    std::vector <int> range1;
    std::vector <int> range2;
    std::string kernel_name;
};

#define CASE_GEMM_INT8_NN_TRANSPOSITION 64, 64, 64, 1, 2, 1, 2, 1, 2, 1, 2, false, false, \
1.5f, 2.0f, data_types::i8, data_types::u8, data_types::f32, data_types::f32, {-128, 127, 1}, {0, 255, 1}, {-10, 10, 8}
#define CASE_GEMM_INT8_NT_TRANSPOSITION 32, 64, 32, 2, 1, 2, 1, 2, 1, 2, 1, false, true, \
1.7f, 1.3f, data_types::i8, data_types::u8, data_types::f32, data_types::f32, {-128, 127, 1}, {0, 255, 1}, {-10, 10, 8}
#define CASE_GEMM_INT8_TN_TRANSPOSITION 128, 64, 32, 2, 2, 2, 2, 2, 2, 2, 2, true, false, \
1.0f, 0.0f, data_types::i8, data_types::u8, data_types::f32, data_types::f32, {-128, 127, 1}, {0, 255, 1}, {-10, 10, 8}
#define CASE_GEMM_INT8_TT_TRANSPOSITION 32, 32, 32, 1, 1, 1, 1, 1, 1, 1, 1, true, true, \
1.2f, 0.5f, data_types::i8, data_types::u8, data_types::f32, data_types::f32, {-128, 127, 1}, {0, 255, 1}, {-10, 10, 8}

#define CASE_GEMM_INT8_BROADCAST_1 32, 32, 32, 1, 2, 1, 1, 1, 1, 1, 2, false, false, \
1.5f, 2.0f, data_types::i8, data_types::u8, data_types::f32, data_types::f32, {-128, 127, 1}, {0, 255, 1}, {-10, 10, 8}
#define CASE_GEMM_INT8_BROADCAST_2 32, 32, 64, 2, 1, 1, 1, 1, 1, 2, 1, false, false, \
1.7f, 1.3f, data_types::i8, data_types::u8, data_types::f32, data_types::f32, {-128, 127, 1}, {0, 255, 1}, {-10, 10, 8}
#define CASE_GEMM_INT8_BROADCAST_3 64, 32, 32, 1, 2, 2, 1, 1, 2, 2, 2, false, false, \
1.0f, 1.5f, data_types::i8, data_types::u8, data_types::f32, data_types::f32, {-128, 127, 1}, {0, 255, 1}, {-10, 10, 8}
#define CASE_GEMM_INT8_BROADCAST_4 32, 64, 32, 1, 1, 2, 2, 2, 2, 2, 2, false, false, \
1.2f, 0.5f, data_types::i8, data_types::u8, data_types::f32, data_types::f32, {-128, 127, 1}, {0, 255, 1}, {-10, 10, 8}

#define CASE_GEMM_INT8_LEFTOVERS_1 13, 32, 32, 1, 1, 1, 1, 1, 1, 1, 1, false, false, \
1.5f, 2.0f, data_types::i8, data_types::u8, data_types::f32, data_types::f32, {-128, 127, 1}, {0, 255, 1}, {-10, 10, 8}
#define CASE_GEMM_INT8_LEFTOVERS_2 13, 32, 32, 1, 1, 1, 1, 1, 1, 1, 1, false, true, \
1.6f, 1.0f, data_types::i8, data_types::u8, data_types::f32, data_types::f32, {-128, 127, 1}, {0, 255, 1}, {-10, 10, 8}
#define CASE_GEMM_INT8_LEFTOVERS_3 13, 32, 32, 1, 1, 1, 1, 1, 1, 1, 1, true, false, \
1.0f, 1.5f, data_types::i8, data_types::u8, data_types::f32, data_types::f32, {-128, 127, 1}, {0, 255, 1}, {-10, 10, 8}
#define CASE_GEMM_INT8_LEFTOVERS_4 13, 32, 32, 1, 1, 1, 1, 1, 1, 1, 1, true, true, \
1.7f, 1.3f, data_types::i8, data_types::u8, data_types::f32, data_types::f32, {-128, 127, 1}, {0, 255, 1}, {-10, 10, 8}
#define CASE_GEMM_INT8_LEFTOVERS_5 32, 13, 32, 1, 1, 1, 1, 1, 1, 1, 1, false, false, \
1.5f, 2.0f, data_types::i8, data_types::u8, data_types::f32, data_types::f32, {-128, 127, 1}, {0, 255, 1}, {-10, 10, 8}
#define CASE_GEMM_INT8_LEFTOVERS_6 32, 13, 32, 1, 1, 1, 1, 1, 1, 1, 1, false, true, \
1.6f, 1.0f, data_types::i8, data_types::u8, data_types::f32, data_types::f32, {-128, 127, 1}, {0, 255, 1}, {-10, 10, 8}
#define CASE_GEMM_INT8_LEFTOVERS_7 32, 13, 32, 1, 1, 1, 1, 1, 1, 1, 1, true, false, \
1.0f, 1.5f, data_types::i8, data_types::u8, data_types::f32, data_types::f32, {-128, 127, 1}, {0, 255, 1}, {-10, 10, 8}
#define CASE_GEMM_INT8_LEFTOVERS_8 32, 13, 32, 1, 1, 1, 1, 1, 1, 1, 1, true, true, \
1.7f, 1.3f, data_types::i8, data_types::u8, data_types::f32, data_types::f32, {-128, 127, 1}, {0, 255, 1}, {-10, 10, 8}
#define CASE_GEMM_INT8_LEFTOVERS_9 32, 32, 13, 1, 1, 1, 1, 1, 1, 1, 1, false, false, \
1.5f, 2.0f, data_types::i8, data_types::u8, data_types::f32, data_types::f32, {-128, 127, 1}, {0, 255, 1}, {-10, 10, 8}
#define CASE_GEMM_INT8_LEFTOVERS_10 32, 32, 13, 1, 1, 1, 1, 1, 1, 1, 1, false, true, \
1.6f, 1.0f, data_types::i8, data_types::u8, data_types::f32, data_types::f32, {-128, 127, 1}, {0, 255, 1}, {-10, 10, 8}
#define CASE_GEMM_INT8_LEFTOVERS_11 32, 32, 13, 1, 1, 1, 1, 1, 1, 1, 1, true, false, \
1.0f, 1.5f, data_types::i8, data_types::u8, data_types::f32, data_types::f32, {-128, 127, 1}, {0, 255, 1}, {-10, 10, 8}
#define CASE_GEMM_INT8_LEFTOVERS_12 32, 32, 13, 1, 1, 1, 1, 1, 1, 1, 1, true, true, \
1.7f, 1.3f, data_types::i8, data_types::u8, data_types::f32, data_types::f32, {-128, 127, 1}, {0, 255, 1}, {-10, 10, 8}

#define CASE_GEMM_INT8_COMBO_1 8, 8, 32, 1, 2, 1, 1, 1, 1, 1, 2, false, false, \
1.5f, 2.0f, data_types::i8, data_types::u8, data_types::f32, data_types::f32, {-128, 127, 1}, {0, 255, 1}, {-10, 10, 8}
#define CASE_GEMM_INT8_COMBO_2 16, 16, 64, 2, 1, 1, 1, 1, 1, 2, 1, false, true, \
1.7f, 0.0f, data_types::i8, data_types::u8, data_types::f32, data_types::f32, {-128, 127, 1}, {0, 255, 1}, {-10, 10, 8}
#define CASE_GEMM_INT8_COMBO_3 11, 31, 21, 7, 15, 7, 15, 7, 15, 7, 15, true, false, \
1.0f, 1.5f, data_types::i8, data_types::u8, data_types::f32, data_types::f32, {-128, 127, 1}, {0, 255, 1}, {-10, 10, 8}
#define CASE_GEMM_INT8_COMBO_4 32, 32, 32, 3, 6, 3, 6, 3, 6, 3, 6, true, true, \
1.2f, 4.0f, data_types::i8, data_types::u8, data_types::f32, data_types::f32, {-128, 127, 1}, {0, 255, 1}, {-10, 10, 8}

#define CASE_GEMM_INT8_SLM_COMBO_1 64, 64, 64, 1, 2, 1, 1, 1, 1, 1, 2, false, false, \
1.5f, 2.0f, data_types::i8, data_types::u8, data_types::f32, data_types::f32, {-128, 127, 1}, {0, 255, 1}, {-10, 10, 8}
#define CASE_GEMM_INT8_SLM_COMBO_2 384, 384, 64, 2, 1, 1, 1, 1, 1, 2, 1, false, false, \
1.7f, 0.0f, data_types::i8, data_types::u8, data_types::f32, data_types::f32, {-128, 127, 1}, {0, 255, 1}, {-10, 10, 8}
#define CASE_GEMM_INT8_SLM_COMBO_3 128, 128, 64, 2, 3, 2, 3, 2, 3, 2, 3, false, false, \
1.0f, 1.5f, data_types::i8, data_types::u8, data_types::f32, data_types::f32, {-128, 127, 1}, {0, 255, 1}, {-10, 10, 8}
#define CASE_GEMM_INT8_SLM_COMBO_4 256, 64, 64, 3, 6, 3, 6, 3, 6, 3, 6, false, false, \
1.2f, 4.0f, data_types::i8, data_types::u8, data_types::f32, data_types::f32, {-128, 127, 1}, {0, 255, 1}, {-10, 10, 8}

#define CASE_GEMM_FP32_TILED_NN_1 32, 32, 32, 1, 1, 1, 1, 1, 1, 1, 1, false, false, \
1.5f, 2.0f, data_types::f32, data_types::f32, data_types::f32, data_types::f32, {-10, 10, 8}, {-10, 10, 8}, {-10, 10, 8}
#define CASE_GEMM_FP32_TILED_NN_2 64, 64, 64, 1, 1, 1, 1, 1, 1, 1, 1, false, false, \
1.7f, 0.0f, data_types::f32, data_types::f32, data_types::f32, data_types::f32, {-10, 10, 8}, {-10, 10, 8}, {-10, 10, 8}
#define CASE_GEMM_FP32_TILED_NN_3 31, 47, 65, 1, 1, 1, 1, 1, 1, 1, 1, false, false, \
1.0f, 1.5f, data_types::f32, data_types::f32, data_types::f32, data_types::f32, {-10, 10, 8}, {-10, 10, 8}, {-10, 10, 8}
#define CASE_GEMM_FP32_TILED_NN_4 65, 31, 47, 1, 1, 1, 1, 1, 1, 1, 1, false, false, \
1.0f, 4.0f, data_types::f32, data_types::f32, data_types::f32, data_types::f32, {-10, 10, 8}, {-10, 10, 8}, {-10, 10, 8}

#define CASE_GEMM_FP32_TILED_NT_1 16, 16, 16, 1, 1, 1, 1, 1, 1, 1, 1, false, true, \
1.5f, 2.0f, data_types::f32, data_types::f32, data_types::f32, data_types::f32, {-10, 10, 8}, {-10, 10, 8}, {-10, 10, 8}
#define CASE_GEMM_FP32_TILED_NT_2 32, 32, 32, 1, 1, 1, 1, 1, 1, 1, 1, false, true, \
1.7f, 0.0f, data_types::f32, data_types::f32, data_types::f32, data_types::f32, {-10, 10, 8}, {-10, 10, 8}, {-10, 10, 8}
#define CASE_GEMM_FP32_TILED_NT_3 64, 32, 64, 1, 1, 1, 1, 1, 1, 1, 1, false, true, \
1.0f, 1.5f, data_types::f32, data_types::f32, data_types::f32, data_types::f32, {-10, 10, 8}, {-10, 10, 8}, {-10, 10, 8}
#define CASE_GEMM_FP32_TILED_NT_4 16, 128, 64, 1, 1, 1, 1, 1, 1, 1, 1, false, true, \
1.0f, 4.0f, data_types::f32, data_types::f32, data_types::f32, data_types::f32, {-10, 10, 8}, {-10, 10, 8}, {-10, 10, 8}

#define CASE_GEMM_FP32_TILED_TN_1 16, 16, 16, 1, 1, 1, 1, 1, 1, 1, 1, true, false, \
1.5f, 2.0f, data_types::f32, data_types::f32, data_types::f32, data_types::f32, {-10, 10, 8}, {-10, 10, 8}, {-10, 10, 8}
#define CASE_GEMM_FP32_TILED_TN_2 32, 32, 32, 1, 1, 1, 1, 1, 1, 1, 1, true, false, \
1.7f, 0.0f, data_types::f32, data_types::f32, data_types::f32, data_types::f32, {-10, 10, 8}, {-10, 10, 8}, {-10, 10, 8}
#define CASE_GEMM_FP32_TILED_TN_3 64, 32, 64, 1, 1, 1, 1, 1, 1, 1, 1, true, false, \
1.0f, 1.5f, data_types::f32, data_types::f32, data_types::f32, data_types::f32, {-10, 10, 8}, {-10, 10, 8}, {-10, 10, 8}
#define CASE_GEMM_FP32_TILED_TN_4 16, 128, 64, 1, 1, 1, 1, 1, 1, 1, 1, true, false, \
1.0f, 4.0f, data_types::f32, data_types::f32, data_types::f32, data_types::f32, {-10, 10, 8}, {-10, 10, 8}, {-10, 10, 8}

#define CASE_GEMM_FP32_TILED_TT_1 16, 16, 16, 1, 1, 1, 1, 1, 1, 1, 1, true, true, \
1.5f, 2.0f, data_types::f32, data_types::f32, data_types::f32, data_types::f32, {-10, 10, 8}, {-10, 10, 8}, {-10, 10, 8}
#define CASE_GEMM_FP32_TILED_TT_2 32, 32, 32, 1, 1, 1, 1, 1, 1, 1, 1, true, true, \
1.7f, 0.0f, data_types::f32, data_types::f32, data_types::f32, data_types::f32, {-10, 10, 8}, {-10, 10, 8}, {-10, 10, 8}
#define CASE_GEMM_FP32_TILED_TT_3 64, 32, 64, 1, 1, 1, 1, 1, 1, 1, 1, true, true, \
1.0f, 1.5f, data_types::f32, data_types::f32, data_types::f32, data_types::f32, {-10, 10, 8}, {-10, 10, 8}, {-10, 10, 8}
#define CASE_GEMM_FP32_TILED_TT_4 16, 128, 64, 1, 1, 1, 1, 1, 1, 1, 1, true, true, \
1.0f, 4.0f, data_types::f32, data_types::f32, data_types::f32, data_types::f32, {-10, 10, 8}, {-10, 10, 8}, {-10, 10, 8}

#define CASE_GEMM_FP32_TILED_NN_BROADCAST_1 64, 96, 32, 1, 2, 1, 1, 1, 1, 1, 2, false, false, \
1.5f, 2.0f, data_types::f32, data_types::f32, data_types::f32, data_types::f32, {-10, 10, 8}, {-10, 10, 8}, {-10, 10, 8}
#define CASE_GEMM_FP32_TILED_NN_BROADCAST_2 32, 16, 16, 2, 1, 1, 1, 1, 1, 2, 1, false, false, \
1.7f, 0.0f, data_types::f32, data_types::f32, data_types::f32, data_types::f32, {-10, 10, 8}, {-10, 10, 8}, {-10, 10, 8}
#define CASE_GEMM_FP32_TILED_NN_BROADCAST_3 5, 1, 3, 1, 2, 2, 1, 1, 2, 2, 2, false, false, \
1.0f, 1.5f, data_types::f32, data_types::f32, data_types::f32, data_types::f32, {-10, 10, 8}, {-10, 10, 8}, {-10, 10, 8}
#define CASE_GEMM_FP32_TILED_NN_BROADCAST_4 64, 1, 2, 1, 1, 2, 2, 2, 2, 2, 2, false, false, \
1.0f, 4.0f, data_types::f32, data_types::f32, data_types::f32, data_types::f32, {-10, 10, 8}, {-10, 10, 8}, {-10, 10, 8}

#define CASE_GEMM_FP16_TILED_NN_1 64, 32, 32, 1, 1, 1, 1, 1, 1, 1, 1, false, false, \
1.5f, 2.0f, data_types::f16, data_types::f16, data_types::f16, data_types::f16, {-1, 1, 1}, {-1, 1, 1}, {-1, 1, 1}
#define CASE_GEMM_FP16_TILED_NN_2 128, 64, 64, 1, 1, 1, 1, 1, 1, 1, 1, false, false, \
1.7f, 0.0f, data_types::f16, data_types::f16, data_types::f16, data_types::f16, {-1, 1, 1}, {-1, 1, 1}, {-1, 1, 1}
#define CASE_GEMM_FP16_TILED_NN_3 131, 17, 15, 1, 1, 1, 1, 1, 1, 1, 1, false, false, \
1.0f, 1.5f, data_types::f16, data_types::f16, data_types::f16, data_types::f16, {-1, 1, 1}, {-1, 1, 1}, {-1, 1, 1}
#define CASE_GEMM_FP16_TILED_NN_4 33, 17, 17, 1, 1, 1, 1, 1, 1, 1, 1, false, false, \
1.0f, 4.0f, data_types::f16, data_types::f16, data_types::f16, data_types::f16, {-1, 1, 1}, {-1, 1, 1}, {-1, 1, 1}

#define CASE_GEMM_FP16_TILED_NT_1 16, 16, 16, 1, 1, 1, 1, 1, 1, 1, 1, false, true, \
1.5f, 2.0f, data_types::f16, data_types::f16, data_types::f16, data_types::f16, {-1, 1, 1}, {-1, 1, 1}, {-1, 1, 1}
#define CASE_GEMM_FP16_TILED_NT_2 32, 32, 32, 1, 1, 1, 1, 1, 1, 1, 1, false, true, \
1.7f, 0.0f, data_types::f16, data_types::f16, data_types::f16, data_types::f16, {-1, 1, 1}, {-1, 1, 1}, {-1, 1, 1}
#define CASE_GEMM_FP16_TILED_NT_3 64, 32, 64, 1, 1, 1, 1, 1, 1, 1, 1, false, true, \
1.0f, 1.5f, data_types::f16, data_types::f16, data_types::f16, data_types::f16, {-1, 1, 1}, {-1, 1, 1}, {-1, 1, 1}
#define CASE_GEMM_FP16_TILED_NT_4 16, 128, 64, 1, 1, 1, 1, 1, 1, 1, 1, false, true, \
1.0f, 4.0f, data_types::f16, data_types::f16, data_types::f16, data_types::f16, {-1, 1, 1}, {-1, 1, 1}, {-1, 1, 1}

#define CASE_GEMM_FP16_TILED_TN_1 16, 16, 16, 1, 1, 1, 1, 1, 1, 1, 1, true, false, \
1.5f, 2.0f, data_types::f16, data_types::f16, data_types::f16, data_types::f16, {-1, 1, 1}, {-1, 1, 1}, {-1, 1, 1}
#define CASE_GEMM_FP16_TILED_TN_2 32, 32, 32, 1, 1, 1, 1, 1, 1, 1, 1, true, false, \
1.7f, 0.0f, data_types::f16, data_types::f16, data_types::f16, data_types::f16, {-1, 1, 1}, {-1, 1, 1}, {-1, 1, 1}
#define CASE_GEMM_FP16_TILED_TN_3 64, 32, 64, 1, 1, 1, 1, 1, 1, 1, 1, true, false, \
1.0f, 1.5f, data_types::f16, data_types::f16, data_types::f16, data_types::f16, {-1, 1, 1}, {-1, 1, 1}, {-1, 1, 1}
#define CASE_GEMM_FP16_TILED_TN_4 16, 128, 64, 1, 1, 1, 1, 1, 1, 1, 1, true, false, \
1.0f, 4.0f, data_types::f16, data_types::f16, data_types::f16, data_types::f16, {-1, 1, 1}, {-1, 1, 1}, {-1, 1, 1}

#define CASE_GEMM_FP16_TILED_TT_1 16, 16, 16, 1, 1, 1, 1, 1, 1, 1, 1, true, true, \
1.5f, 2.0f, data_types::f16, data_types::f16, data_types::f16, data_types::f16, {-1, 1, 1}, {-1, 1, 1}, {-1, 1, 1}
#define CASE_GEMM_FP16_TILED_TT_2 32, 32, 32, 1, 1, 1, 1, 1, 1, 1, 1, true, true, \
1.7f, 0.0f, data_types::f16, data_types::f16, data_types::f16, data_types::f16, {-1, 1, 1}, {-1, 1, 1}, {-1, 1, 1}
#define CASE_GEMM_FP16_TILED_TT_3 64, 32, 64, 1, 1, 1, 1, 1, 1, 1, 1, true, true, \
1.0f, 1.5f, data_types::f16, data_types::f16, data_types::f16, data_types::f16, {-1, 1, 1}, {-1, 1, 1}, {-1, 1, 1}
#define CASE_GEMM_FP16_TILED_TT_4 16, 128, 64, 1, 1, 1, 1, 1, 1, 1, 1, true, true, \
1.0f, 4.0f, data_types::f16, data_types::f16, data_types::f16, data_types::f16, {-1, 1, 1}, {-1, 1, 1}, {-1, 1, 1}

#define CASE_GEMM_FP16_TILED_NN_BROADCAST_1 64, 96, 128, 1, 2, 1, 1, 1, 1, 1, 2, false, false, \
1.5f, 2.0f, data_types::f16, data_types::f16, data_types::f16, data_types::f16, {-1, 1, 1}, {-1, 1, 1}, {-1, 1, 1}
#define CASE_GEMM_FP16_TILED_NN_BROADCAST_2 64, 16, 64, 2, 1, 1, 1, 1, 1, 2, 1, false, false, \
1.7f, 0.0f, data_types::f16, data_types::f16, data_types::f16, data_types::f16, {-1, 1, 1}, {-1, 1, 1}, {-1, 1, 1}
#define CASE_GEMM_FP16_TILED_NN_BROADCAST_3 1, 2, 3, 1, 2, 2, 1, 1, 2, 2, 2, false, false, \
1.0f, 1.5f, data_types::f16, data_types::f16, data_types::f16, data_types::f16, {-1, 1, 1}, {-1, 1, 1}, {-1, 1, 1}
#define CASE_GEMM_FP16_TILED_NN_BROADCAST_4 8, 8, 8, 1, 1, 2, 2, 2, 2, 2, 2, false, false, \
1.0f, 4.0f, data_types::f16, data_types::f16, data_types::f16, data_types::f16, {-1, 1, 1}, {-1, 1, 1}, {-1, 1, 1}

template <typename gemm_params, typename input0_type, typename input1_type, typename input2_type, typename output_type, typename accumulator_type>
class GemmBaseTest : public ::testing::TestWithParam<gemm_params> {
public:

    inline size_t getGemmIndex(size_t x, size_t y, size_t f, size_t b, size_t x_size, size_t y_size, size_t f_num, size_t b_num,
                               size_t x_pitch, size_t y_pitch, size_t f_pitch, size_t b_pitch) {
        return (x % x_size) * x_pitch + (y % y_size) * y_pitch + (f % f_num) * f_pitch + (b % b_num) * b_pitch;
    }

    void execute(gemm_params& p) {
        auto& engine = get_test_engine();

        auto y0_size = p.m_size;
        auto y0_pitch = p.k_size;
        auto x0_size = p.k_size;
        auto x0_pitch = 1;
        auto f0_pitch = y0_size * x0_size;
        auto b0_pitch = p.f0_num * f0_pitch;

        auto y1_size = p.k_size;
        auto y1_pitch = p.n_size;
        auto x1_size = p.n_size;
        auto x1_pitch = 1;
        auto f1_pitch = y1_size * x1_size;
        auto b1_pitch = p.f1_num * f1_pitch;

        auto y2_size = p.m_size;
        auto y2_pitch = p.n_size;
        auto x2_size = p.n_size;
        auto x2_pitch = 1;
        auto f2_pitch = y2_size * x2_size;
        auto b2_pitch = p.f2_num * f2_pitch;

        auto y_out_size = p.m_size;
        auto y_out_pitch = p.n_size;
        auto x_out_size = p.n_size;
        auto x_out_pitch = 1;
        auto f_out_pitch = y_out_size * x_out_size;
        auto b_out_pitch = p.f_out_num * f_out_pitch;

        if (p.transpose_input0) {
            y0_size = p.k_size;
            y0_pitch = p.m_size;
            x0_size = p.m_size;
            x0_pitch = 1;
        }

        if (p.transpose_input1) {
            y1_size = p.n_size;
            y1_pitch = p.k_size;
            x1_size = p.k_size;
            x1_pitch = 1;
        }

        auto input0_size = tensor((int)p.b0_num, (int)p.f0_num, (int)x0_size, (int)y0_size);
        VVVVF<input0_type> input0_data = generate_random_4d<input0_type>(p.b0_num, p.f0_num, x0_size, y0_size, p.range0[0], p.range0[1], p.range0[2]);
        auto input0_data_bfyx = flatten_4d(format::bfyx, input0_data);
        auto input0_mem = engine.allocate_memory({ p.allocate0_type, format::bfyx, input0_size });
        set_values(input0_mem, input0_data_bfyx);

        auto input1_size = tensor((int)p.b1_num, (int)p.f1_num, (int)x1_size, (int)y1_size);
        VVVVF<input1_type> input1_data = generate_random_4d<input1_type>(p.b1_num, p.f1_num, x1_size, y1_size, p.range1[0], p.range1[1], p.range1[2]);
        auto input1_data_bfyx = flatten_4d(format::bfyx, input1_data);
        auto input1_mem = engine.allocate_memory({ p.allocate1_type, format::bfyx, input1_size });
        set_values(input1_mem, input1_data_bfyx);

        auto input2_size = tensor((int)p.b2_num, (int)p.f2_num, (int)x2_size, (int)y2_size);
        VVVVF<input2_type> input2_data = generate_random_4d<input2_type>(p.b2_num, p.f2_num, x2_size, y2_size, p.range2[0], p.range2[1], p.range2[2]);
        auto input2_data_bfyx = flatten_4d(format::bfyx, input2_data);
        auto input2_mem = engine.allocate_memory({ p.allocate2_type, format::bfyx, input2_size });
        set_values(input2_mem, input2_data_bfyx);

        std::vector<output_type> out_data(p.b_out_num * p.f_out_num * p.m_size * p.n_size);

        for (size_t b = 0; b < p.b_out_num; ++b) {
            for (size_t f = 0; f < p.f_out_num; ++f) {
                for (size_t y = 0; y < p.m_size; ++y) {
                    for (size_t x = 0; x < p.n_size; ++x) {
                        size_t input2_data_index = getGemmIndex(x, y, f, b, x2_size, y2_size, p.f2_num, p.b2_num, x2_pitch, y2_pitch, f2_pitch, b2_pitch);
                        size_t out_data_index = getGemmIndex(x, y, f, b, x_out_size, y_out_size, p.f_out_num, p.b_out_num,
                                                             x_out_pitch, y_out_pitch, f_out_pitch, b_out_pitch);
                        accumulator_type acc = 0;

                        for (size_t k = 0; k < p.k_size; ++k) {
                            size_t input0_data_index = getGemmIndex(k * (!p.transpose_input0) + y * p.transpose_input0, y * (!p.transpose_input0) +
                            k * p.transpose_input0, f, b, x0_size, y0_size, p.f0_num, p.b0_num, x0_pitch, y0_pitch, f0_pitch, b0_pitch);
                            size_t input1_data_index = getGemmIndex(x * (!p.transpose_input1) + k * p.transpose_input1, k * (!p.transpose_input1) +
                            x * p.transpose_input1, f, b, x1_size, y1_size, p.f1_num, p.b1_num, x1_pitch, y1_pitch, f1_pitch, b1_pitch);

                            acc += (accumulator_type)input0_data_bfyx[input0_data_index] * (accumulator_type)input1_data_bfyx[input1_data_index];
                        }

                        out_data[out_data_index] = (output_type)acc;
                        out_data[out_data_index] *= (output_type)p.alpha;
                        out_data[out_data_index] += (output_type)p.beta * (output_type)input2_data_bfyx[input2_data_index];
                    }
                }
            }
        }

        topology topology;
        topology.add(input_layout("input0", input0_mem->get_layout()));
        topology.add(input_layout("input1", input1_mem->get_layout()));
        topology.add(input_layout("input2", input2_mem->get_layout()));
        topology.add(gemm("gemm_bfyx", { "input0", "input1", "input2" }, p.output_type, p.transpose_input0, p.transpose_input1, p.alpha, p.beta));
        topology.add(reorder("reorder_bfyx", "gemm_bfyx", format::bfyx, data_types::f32));

        build_options options;
        implementation_desc gemm_impl = { format::bfyx, p.kernel_name };
        options.set_option(build_option::force_implementations({ {"gemm_bfyx", gemm_impl} }));

        network network(engine, topology, options);
        network.set_input_data("input0", input0_mem);
        network.set_input_data("input1", input1_mem);
        network.set_input_data("input2", input2_mem);
        auto outputs = network.execute();
        auto output = outputs.at("reorder_bfyx").get_memory();
        cldnn::mem_lock<float> output_ptr(output, get_test_stream());

        EXPECT_EQ(output_ptr.size(), (size_t)(p.b_out_num * p.f_out_num * p.m_size * p.n_size));
        if (sizeof(input0_type) == 1) {
            for (size_t i = 0; i < out_data.size(); ++i) {
                EXPECT_NEAR(float(output_ptr[i]), float(out_data[i]), 1e-1) << "index = " << i;
            }
        } else if (sizeof(input0_type) == 2) {
            for (size_t i = 0; i < out_data.size(); ++i) {
                EXPECT_NEAR(float(output_ptr[i]), float(out_data[i]), 1e-1) << "index = " << i;
            }
        } else {
            for (size_t i = 0; i < out_data.size(); ++i) {
                EXPECT_NEAR(float(output_ptr[i]), float(out_data[i]), 3e-4) << "index = " << i;
            }
        }
    }
};

class gemm_int8_transposition_tests : public ::GemmBaseTest<gemm_base_test_params, int8_t, uint8_t, float, float, int32_t> {};
TEST_P(gemm_int8_transposition_tests, basic) { auto p = GetParam(); execute(p); }

INSTANTIATE_TEST_SUITE_P(gemm_gpu, gemm_int8_transposition_tests, ::testing::ValuesIn(std::vector <gemm_base_test_params> {
                        gemm_base_test_params{ CASE_GEMM_INT8_NN_TRANSPOSITION, "gemm_mmad_int8" },
                        gemm_base_test_params{ CASE_GEMM_INT8_NT_TRANSPOSITION, "gemm_mmad_int8" },
                        gemm_base_test_params{ CASE_GEMM_INT8_TN_TRANSPOSITION, "gemm_mmad_int8" },
                        gemm_base_test_params{ CASE_GEMM_INT8_TT_TRANSPOSITION, "gemm_mmad_int8" },
}));

class gemm_int8_broadcast_tests : public ::GemmBaseTest<gemm_base_test_params, int8_t, uint8_t, float, float, int32_t> {};
TEST_P(gemm_int8_broadcast_tests, basic) { auto p = GetParam(); execute(p); }

INSTANTIATE_TEST_SUITE_P(gemm_gpu, gemm_int8_broadcast_tests, ::testing::ValuesIn(std::vector <gemm_base_test_params> {
                        gemm_base_test_params{ CASE_GEMM_INT8_BROADCAST_1, "gemm_mmad_int8" },
                        gemm_base_test_params{ CASE_GEMM_INT8_BROADCAST_2, "gemm_mmad_int8" },
                        gemm_base_test_params{ CASE_GEMM_INT8_BROADCAST_3, "gemm_mmad_int8" },
                        gemm_base_test_params{ CASE_GEMM_INT8_BROADCAST_4, "gemm_mmad_int8" },
}));

class gemm_int8_leftovers_tests : public ::GemmBaseTest<gemm_base_test_params, int8_t, uint8_t, float, float, int32_t> {};
TEST_P(gemm_int8_leftovers_tests, basic) { auto p = GetParam(); execute(p); }

INSTANTIATE_TEST_SUITE_P(gemm_gpu, gemm_int8_leftovers_tests, ::testing::ValuesIn(std::vector <gemm_base_test_params> {
                        gemm_base_test_params{ CASE_GEMM_INT8_LEFTOVERS_1, "gemm_mmad_int8" },
                        gemm_base_test_params{ CASE_GEMM_INT8_LEFTOVERS_2, "gemm_mmad_int8" },
                        gemm_base_test_params{ CASE_GEMM_INT8_LEFTOVERS_3, "gemm_mmad_int8" },
                        gemm_base_test_params{ CASE_GEMM_INT8_LEFTOVERS_4, "gemm_mmad_int8" },
                        gemm_base_test_params{ CASE_GEMM_INT8_LEFTOVERS_5, "gemm_mmad_int8" },
                        gemm_base_test_params{ CASE_GEMM_INT8_LEFTOVERS_6, "gemm_mmad_int8" },
                        gemm_base_test_params{ CASE_GEMM_INT8_LEFTOVERS_7, "gemm_mmad_int8" },
                        gemm_base_test_params{ CASE_GEMM_INT8_LEFTOVERS_8, "gemm_mmad_int8" },
                        gemm_base_test_params{ CASE_GEMM_INT8_LEFTOVERS_9, "gemm_mmad_int8" },
                        gemm_base_test_params{ CASE_GEMM_INT8_LEFTOVERS_10, "gemm_mmad_int8" },
                        gemm_base_test_params{ CASE_GEMM_INT8_LEFTOVERS_11, "gemm_mmad_int8" },
                        gemm_base_test_params{ CASE_GEMM_INT8_LEFTOVERS_12, "gemm_mmad_int8" },
}));

class gemm_int8_combo_tests : public ::GemmBaseTest<gemm_base_test_params, int8_t, uint8_t, float, float, int32_t> {};
TEST_P(gemm_int8_combo_tests, basic) { auto p = GetParam(); execute(p); }

INSTANTIATE_TEST_SUITE_P(gemm_gpu, gemm_int8_combo_tests, ::testing::ValuesIn(std::vector <gemm_base_test_params> {
                        gemm_base_test_params{ CASE_GEMM_INT8_COMBO_1, "gemm_mmad_int8" },
                        gemm_base_test_params{ CASE_GEMM_INT8_COMBO_2, "gemm_mmad_int8" },
                        gemm_base_test_params{ CASE_GEMM_INT8_COMBO_3, "gemm_mmad_int8" },
                        gemm_base_test_params{ CASE_GEMM_INT8_COMBO_4, "gemm_mmad_int8" },
}));

class gemm_int8_slm_combo_tests : public ::GemmBaseTest<gemm_base_test_params, int8_t, uint8_t, float, float, int32_t> {};
TEST_P(gemm_int8_slm_combo_tests, basic) { auto p = GetParam(); execute(p); }

INSTANTIATE_TEST_SUITE_P(gemm_gpu, gemm_int8_slm_combo_tests, ::testing::ValuesIn(std::vector <gemm_base_test_params> {
                        gemm_base_test_params{ CASE_GEMM_INT8_SLM_COMBO_1, "gemm_mmad_int8_slm" },
                        gemm_base_test_params{ CASE_GEMM_INT8_SLM_COMBO_2, "gemm_mmad_int8_slm" },
                        gemm_base_test_params{ CASE_GEMM_INT8_SLM_COMBO_3, "gemm_mmad_int8_slm" },
                        gemm_base_test_params{ CASE_GEMM_INT8_SLM_COMBO_4, "gemm_mmad_int8_slm" },
}));

class gemm_fp32_tiled_nn_tests : public ::GemmBaseTest<gemm_base_test_params, float, float, float, float, float> {};
TEST_P(gemm_fp32_tiled_nn_tests, basic) { auto p = GetParam(); execute(p); }

INSTANTIATE_TEST_SUITE_P(gemm_gpu, gemm_fp32_tiled_nn_tests, ::testing::ValuesIn(std::vector <gemm_base_test_params> {
                        gemm_base_test_params{ CASE_GEMM_FP32_TILED_NN_1, "gemm_tiled_opt" },
                        gemm_base_test_params{ CASE_GEMM_FP32_TILED_NN_2, "gemm_tiled_opt" },
                        gemm_base_test_params{ CASE_GEMM_FP32_TILED_NN_3, "gemm_tiled_opt" },
                        gemm_base_test_params{ CASE_GEMM_FP32_TILED_NN_4, "gemm_tiled_opt" },
}));

class gemm_fp32_tiled_nt_tests : public ::GemmBaseTest<gemm_base_test_params, float, float, float, float, float> {};
TEST_P(gemm_fp32_tiled_nt_tests, basic) { auto p = GetParam(); execute(p); }

INSTANTIATE_TEST_SUITE_P(gemm_gpu, gemm_fp32_tiled_nt_tests, ::testing::ValuesIn(std::vector <gemm_base_test_params> {
                        gemm_base_test_params{ CASE_GEMM_FP32_TILED_NT_1, "gemm_tiled_opt" },
                        gemm_base_test_params{ CASE_GEMM_FP32_TILED_NT_2, "gemm_tiled_opt" },
                        gemm_base_test_params{ CASE_GEMM_FP32_TILED_NT_3, "gemm_tiled_opt" },
                        gemm_base_test_params{ CASE_GEMM_FP32_TILED_NT_4, "gemm_tiled_opt" },
}));

class gemm_fp32_tiled_tn_tests : public ::GemmBaseTest<gemm_base_test_params, float, float, float, float, float> {};
TEST_P(gemm_fp32_tiled_tn_tests, basic) { auto p = GetParam(); execute(p); }

INSTANTIATE_TEST_SUITE_P(gemm_gpu, gemm_fp32_tiled_tn_tests, ::testing::ValuesIn(std::vector <gemm_base_test_params> {
                        gemm_base_test_params{ CASE_GEMM_FP32_TILED_TN_1, "gemm_tiled_opt" },
                        gemm_base_test_params{ CASE_GEMM_FP32_TILED_TN_2, "gemm_tiled_opt" },
                        gemm_base_test_params{ CASE_GEMM_FP32_TILED_TN_3, "gemm_tiled_opt" },
                        gemm_base_test_params{ CASE_GEMM_FP32_TILED_TN_4, "gemm_tiled_opt" },
}));

class gemm_fp32_tiled_tt_tests : public ::GemmBaseTest<gemm_base_test_params, float, float, float, float, float> {};
TEST_P(gemm_fp32_tiled_tt_tests, basic) { auto p = GetParam(); execute(p); }

INSTANTIATE_TEST_SUITE_P(gemm_gpu, gemm_fp32_tiled_tt_tests, ::testing::ValuesIn(std::vector <gemm_base_test_params> {
                        gemm_base_test_params{ CASE_GEMM_FP32_TILED_TT_1, "gemm_tiled_opt" },
                        gemm_base_test_params{ CASE_GEMM_FP32_TILED_TT_2, "gemm_tiled_opt" },
                        gemm_base_test_params{ CASE_GEMM_FP32_TILED_TT_3, "gemm_tiled_opt" },
                        gemm_base_test_params{ CASE_GEMM_FP32_TILED_TT_4, "gemm_tiled_opt" },
}));

class gemm_fp32_tiled_nn_broadcast_tests : public ::GemmBaseTest<gemm_base_test_params, float, float, float, float, float> {};
TEST_P(gemm_fp32_tiled_nn_broadcast_tests, basic) { auto p = GetParam(); execute(p); }

INSTANTIATE_TEST_SUITE_P(gemm_gpu, gemm_fp32_tiled_nn_broadcast_tests, ::testing::ValuesIn(std::vector <gemm_base_test_params> {
                        gemm_base_test_params{ CASE_GEMM_FP32_TILED_NN_BROADCAST_1, "gemm_tiled_opt" },
                        gemm_base_test_params{ CASE_GEMM_FP32_TILED_NN_BROADCAST_2, "gemm_tiled_opt" },
                        gemm_base_test_params{ CASE_GEMM_FP32_TILED_NN_BROADCAST_3, "gemm_tiled_opt" },
                        gemm_base_test_params{ CASE_GEMM_FP32_TILED_NN_BROADCAST_4, "gemm_tiled_opt" },
}));

class gemm_fp16_tiled_nn_tests : public ::GemmBaseTest<gemm_base_test_params, FLOAT16, FLOAT16, FLOAT16, FLOAT16, FLOAT16> {};
TEST_P(gemm_fp16_tiled_nn_tests, basic) { auto p = GetParam(); execute(p); }

INSTANTIATE_TEST_SUITE_P(gemm_gpu, gemm_fp16_tiled_nn_tests, ::testing::ValuesIn(std::vector <gemm_base_test_params> {
                        gemm_base_test_params{ CASE_GEMM_FP16_TILED_NN_1, "gemm_tiled_opt" },
                        gemm_base_test_params{ CASE_GEMM_FP16_TILED_NN_2, "gemm_tiled_opt" },
                        gemm_base_test_params{ CASE_GEMM_FP16_TILED_NN_3, "gemm_tiled_opt" },
                        gemm_base_test_params{ CASE_GEMM_FP16_TILED_NN_4, "gemm_tiled_opt" },
}));

class gemm_fp16_tiled_nt_tests : public ::GemmBaseTest<gemm_base_test_params, FLOAT16, FLOAT16, FLOAT16, FLOAT16, FLOAT16> {};
TEST_P(gemm_fp16_tiled_nt_tests, basic) { auto p = GetParam(); execute(p); }

INSTANTIATE_TEST_SUITE_P(gemm_gpu, gemm_fp16_tiled_nt_tests, ::testing::ValuesIn(std::vector <gemm_base_test_params> {
                        gemm_base_test_params{ CASE_GEMM_FP16_TILED_NT_1, "gemm_tiled_opt" },
                        gemm_base_test_params{ CASE_GEMM_FP16_TILED_NT_2, "gemm_tiled_opt" },
                        gemm_base_test_params{ CASE_GEMM_FP16_TILED_NT_3, "gemm_tiled_opt" },
                        gemm_base_test_params{ CASE_GEMM_FP16_TILED_NT_4, "gemm_tiled_opt" },
}));

class gemm_fp16_tiled_tn_tests : public ::GemmBaseTest<gemm_base_test_params, FLOAT16, FLOAT16, FLOAT16, FLOAT16, FLOAT16> {};
TEST_P(gemm_fp16_tiled_tn_tests, basic) { auto p = GetParam(); execute(p); }

INSTANTIATE_TEST_SUITE_P(gemm_gpu, gemm_fp16_tiled_tn_tests, ::testing::ValuesIn(std::vector <gemm_base_test_params> {
                        gemm_base_test_params{ CASE_GEMM_FP16_TILED_TN_1, "gemm_tiled_opt" },
                        gemm_base_test_params{ CASE_GEMM_FP16_TILED_TN_2, "gemm_tiled_opt" },
                        gemm_base_test_params{ CASE_GEMM_FP16_TILED_TN_3, "gemm_tiled_opt" },
                        gemm_base_test_params{ CASE_GEMM_FP16_TILED_TN_4, "gemm_tiled_opt" },
}));

class gemm_fp16_tiled_tt_tests : public ::GemmBaseTest<gemm_base_test_params, FLOAT16, FLOAT16, FLOAT16, FLOAT16, FLOAT16> {};
TEST_P(gemm_fp16_tiled_tt_tests, basic) { auto p = GetParam(); execute(p); }

INSTANTIATE_TEST_SUITE_P(gemm_gpu, gemm_fp16_tiled_tt_tests, ::testing::ValuesIn(std::vector <gemm_base_test_params> {
                        gemm_base_test_params{ CASE_GEMM_FP16_TILED_TT_1, "gemm_tiled_opt" },
                        gemm_base_test_params{ CASE_GEMM_FP16_TILED_TT_2, "gemm_tiled_opt" },
                        gemm_base_test_params{ CASE_GEMM_FP16_TILED_TT_3, "gemm_tiled_opt" },
                        gemm_base_test_params{ CASE_GEMM_FP16_TILED_TT_4, "gemm_tiled_opt" },
}));

class gemm_fp16_tiled_nn_broadcast_tests : public ::GemmBaseTest<gemm_base_test_params, FLOAT16, FLOAT16, FLOAT16, FLOAT16, FLOAT16> {};
TEST_P(gemm_fp16_tiled_nn_broadcast_tests, basic) { auto p = GetParam(); execute(p); }

INSTANTIATE_TEST_SUITE_P(gemm_gpu, gemm_fp16_tiled_nn_broadcast_tests, ::testing::ValuesIn(std::vector <gemm_base_test_params> {
                        gemm_base_test_params{ CASE_GEMM_FP16_TILED_NN_BROADCAST_1, "gemm_tiled_opt" },
                        gemm_base_test_params{ CASE_GEMM_FP16_TILED_NN_BROADCAST_2, "gemm_tiled_opt" },
                        gemm_base_test_params{ CASE_GEMM_FP16_TILED_NN_BROADCAST_3, "gemm_tiled_opt" },
                        gemm_base_test_params{ CASE_GEMM_FP16_TILED_NN_BROADCAST_4, "gemm_tiled_opt" },
}));
